{"ID":2856487,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.11639","arxiv_id":"2510.11639","title":"OneRec-Think: In-Text Reasoning for Generative Recommendation","abstract":"The powerful generative capacity of Large Language Models (LLMs) has instigated a paradigm shift in recommendation. However, existing generative models (e.g., OneRec) operate as implicit predictors, critically lacking the capacity for explicit and controllable reasoning-a key advantage of LLMs. To bridge this gap, we propose OneRec-Think, a unified framework that seamlessly integrates dialogue, reasoning, and personalized recommendation. OneRec-Think incorporates: (1) Itemic Alignment: cross-modal Item-Textual Alignment for semantic grounding; (2) Reasoning Activation: Reasoning Scaffolding to activate LLM reasoning within the recommendation context; and (3) Reasoning Enhancement, where we design a recommendation-specific reward function that accounts for the multi-validity nature of user preferences. Experiments across public benchmarks show state-of-the-art performance. Moreover, our proposed \"Think-Ahead\" architecture enables effective industrial deployment on Kuaishou, achieving a 0.159\\% gain in APP Stay Time and validating the practical efficacy of the model's explicit reasoning capability.","short_abstract":"The powerful generative capacity of Large Language Models (LLMs) has instigated a paradigm shift in recommendation. However, existing generative models (e.g., OneRec) operate as implicit predictors, critically lacking the capacity for explicit and controllable reasoning-a key advantage of LLMs. To bridge this gap, we p...","url_abs":"https://arxiv.org/abs/2510.11639","url_pdf":"https://arxiv.org/pdf/2510.11639v2","authors":"[\"Zhanyu Liu\",\"Shiyao Wang\",\"Xingmei Wang\",\"Rongzhou Zhang\",\"Jiaxin Deng\",\"Honghui Bao\",\"Jinghao Zhang\",\"Wuchao Li\",\"Pengfei Zheng\",\"Xiangyu Wu\",\"Yifei Hu\",\"Qigen Hu\",\"Xinchen Luo\",\"Lejian Ren\",\"Zixing Zhang\",\"Qianqian Wang\",\"Kuo Cai\",\"Yunfan Wu\",\"Hongtao Cheng\",\"Zexuan Cheng\",\"Lu Ren\",\"Huanjie Wang\",\"Yi Su\",\"Ruiming Tang\",\"Kun Gai\",\"Guorui Zhou\"]","published":"2025-10-13T17:20:13Z","proceeding":"cs.IR","tasks":"[\"cs.IR\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}